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probe_particle_model [2017/01/26 23:01]
probe_particle_model [2022/01/13 14:15] (current)
krejcio [Inputs] - adding more comments to params.ini
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 +===== Introduction =====
  
 +Probe particle model code is supposed to simulate AFM ( and to some extent STM and inelastic-STM) images obtained with tip modified by an atom or small molecule (such as Xe, CO, CH4, H2). In all cases the actual particle (atom or molecule) is replaced by a spherical model particle and classical potential (Lenard-Jones) is used for description of Pauli repulsion and Van der Waals attraction. ​
 +
 +New code is written in C/Python and can operate in framework of Lennard-Jones forces as well as electrostatic forces, if necessary.
 +
 +{{:​ptcda_df.png|}}
 +
 +===== Older Fortran Version =====
 +
 +[[Older documentation]]
 +
 +
 +===== New Version =====
 +
 +The documentation is for "​Master"​ branch, that can be downloaded from [[http://​github.com/​ProkopHapala/​ProbeParticleModel/​]] or by running:
 +  git clone http://​github.com/​ProkopHapala/​ProbeParticleModel/​
 +in your terminal.
 +
 +It should be working for developers "​dev"​ branch, too.
 +
 +It can be downloaded from [[http://​github.com/​ProkopHapala/​ProbeParticleModel/​tree/​dev]] or simply from terminal by running this commands:
 +  git clone http://​github.com/​ProkopHapala/​ProbeParticleModel/​
 +  cd ProbeParticleModel
 +  git checkout dev
 +
 +===== Software requirements =====
 +
 +python-2.7; python-2.7-numpy(-1.8);​ gcc(-4.8); python-2.7-matplotlib(-1.3) ​ - for plotting of figures;
 +
 +== Metacentrum ==
 +
 +  module add python27-modules-intel
 +  module add scipy-0.17.1-py2.7.10
 +
 +And don't forget to add:
 +  import matplotlib as mpl;  mpl.use('​Agg'​);​
 +on the 3rd line of __plot_results.py__,​ if it is not allready in the script and if you want to use it on a cluster. This makes it run without Xserver (e.g. on supercomputer) # see http://​stackoverflow.com/​questions/​4931376/​generating-matplotlib-graphs-without-a-running-x-server
 +
 +===== Hartree potential creation =====
 +
 +[[DFT inputs]]
 +
 +===== Inputs =====
 +
 +== Geometry ==
 +
 +The geometry of the sample can be read from *.bas or *.xyz files, which has to have **xyz extension**! Here we show part of the geometry file from example attached to the model:
 +
 +  71
 +  ​
 +  C       ​0.165 ​  ​0.165 ​  ​0.165 ​  ​-0.0132352941
 +  C       ​2.2987 ​ 1.39372 0.16643 -0.0132352941
 +  C       ​4.4293 ​ 2.62743 0.16468 -0.0132352941
 +  C       ​6.56208 3.85683 0.16431 -0.0132352941
 +  C       ​8.69719 5.08888 0.16545 -0.0132352941
 +  ...
 +
 +Which is in format:
 +
 +Number of atoms
 +optional line
 +Symbol/​or/​Z-of-element x y z charge-optional
 +
 +The Lennard-Jones (L-J) potential needed for calculations can be created by running:
 +  python PATH_TO_YOUR_PROBE_PARTICLE_MODEL/​generateLJFF.py -i YOUR_INPUT_FILE.xyz
 +If charges are also in the input file add "​-q"​ flag to create electrostatic field.
 +
 +Optionally, the geometry can be also read from *.xsf or *.cube file, too. The command for creation of L-J force field then looks like:
 +  python PATH_TO_YOUR_PROBE_PARTICLE_MODEL/​generateLJFF.py -i YOUR_INPUT_FILE.xsf
 +or
 +  python PATH_TO_YOUR_PROBE_PARTICLE_MODEL/​generateLJFF.py -i YOUR_INPUT_FILE.cube
 +
 +
 +x, y and z components of L-J forces are stored in __LJFF_x.xsf__,​ __LJFF_y.xsf__ and __LJFF_z.xsf__ files, respectively. These files that can be viewed e.g. via XCrySDen (http://​www.xcrysden.org/​) or VESTA (http://​jp-minerals.org/​vesta/​en/​).
 +
 +
 +== Hartree potential ==
 +
 +If an electrostatic Hartree potential is obtained from some DFT calculations,​ it can be read *.xsf or *.cube files. The electrostatic force field is created by running:
 +  python PATH_TO_YOUR_PROBE_PARTICLE_MODEL/​generateElFF.py -i YOUR_INPUT_FILE
 +
 +If default parameters are used, than you have monopole represented by an Gaussian cloud of charge with its FWHM of 0.7 Ǎ. The monopole can be changed to non-tilting dipoles or quadrupoles by adding flag: -t type, where type ∈ {s,​px,​py,​pz,​dx2,​dy2,​dz2,​dxy,​dxz,​dyz};​ s stands for monopole (default), p for dipoles, d for quadrupoles. The FWHM of the Gaussian cloud can be changed by adding flag: -s FWHM.
 +
 +== params.ini ==
 +
 +This files contains all important information about the scan and informations for creation of important forcefields. Here we show an example of it:
 +  probeType ​      ​8 ​                              # atom type of ProbeParticle (to choose L-J potential ),e.g. 8 for CO, 54 for Xe  ​
 +  tip            '​dz2' ​                           # For calculations with electrostatics only - multipole of the PP {'​dz2'​ is the most popular now fo CO}, charge cloud is not tilting ​ #
 +  sigma           ​0.71 ​                           # For calculations with electrostatics only - FWHM of the gaussian charge cloud {0.7 or 0.71 are standarts} ​ #
 +  charge ​        ​-0.05 ​                           # For calculations with electrostatics only: if 0.00 then ElFF is not even read - effective charge of probe particle [e] {for multipoles the real moment is q*sigma - dipole - or q*sigma**2 - quadrupole} {for CO '​dz2'​ we typically use -0.30 - -0.05} ​ #
 +  stiffness ​      0.20 0.20 20.00                 # [N/m] harmonic spring potential (x,y,R) components, x,y is bending stiffness, R particle-tip bond-length stiffness, {for CO we typically use 0.24 0.24 20.00}
 +  r0Probe ​        0.0 0.0  3.00                   # [Å] equilibirum position of probe particle (x,y,R) components, R is bond length {3.00 for CO mostly these days}, x,y introduce tip asymmetry
 +  PBC             ​True ​                           # Periodic boundary conditions ? [ True/False ]
 +  gridN           240 240 200                     # Grid division around each cell axis; Not necessary - if it is not here a 0.1 division is applied
 +  gridA   ​23.10994667 ​  ​0.000000 ​     0.000000 ​   # lattice vector of the cell; If geometry is read from .xsf or .cube
 +  gridB   ​11.55497333 ​ 20.01380089 ​   0.000000 ​   # !!!! If geometry is read from *.xyz, but electrostatics from .xsf or .cube than gridN and gridA/B/C has
 +  gridC    0.000000 ​    ​0.000000 ​   20.000000 ​    # to be in agreement with the harteee potential. Also the shift vector in the cube file has to be 0.0 0.0 0.0 !!!! 
 +  scanMin ​    ​00.0 ​  ​00.0 ​   10.0                 # start of scanning (x,y,z) (z should be something like: the highest atom of the sample + R + 2.5)
 +  scanMax ​    ​30.0 ​  ​22.0 ​   15.0                 # end of scanning (x,y,z)
 +  scanStep ​   0.1   ​0.1 ​   0.10                   # steps of scan (dx, dy, dz)
 +  Amplitude ​      ​1.0 ​                            # [Å] oscillation amplitude for conversion Fz->df
 +
 +If you want to make a scan for different probe, you have to change the probeType in __params.ini__ and to recompute L-J forces.
 +
 +**The number of grid divisions in *.xsf files is enlarged by one in each direction. Therefore, gridN have to be numbers of cubicles in *.xsf file reduced by one, if geometry is read from *.xyz, but electrostatics from .xsf**
 +
 +===== Simulating AFM =====
 +
 +With having L-J and electrostatic forces made by generating scripts, you can try to run an AFM scan via:
 +  python PATH_TO_YOUR_PROBE_PARTICLE_MODEL/​relaxed_scan.py
 +which run the scan with charge Q and lateral stiffness K written in __params.ini__. Please note, that electrostatic forces are necessary only if Q ≠ 0.0.  The result - Fz force acting on the tip  -- is saved in __Q?​.??​K?​.??​__ directory as an __OutFz.xsf__ file.
 +The df results for constant height scans can be plotted by:
 +  python PATH_TO_YOUR_PROBE_PARTICLE_MODEL/​plot_results.py ​ --df
 +that plot results for oscillation written in __params.ini__. The results - __df_???​.png__ maps for each tip height - are in directory: __Q?​.??​K?​.??/​Amp?​.??​__
 +
 +optionally WSxM files for each height can be written by putting flag - -WSxM behind the plotting command. Outputs are __df_???​.xyz__ files with WSxM head and x y df data. If - -save_df flag is applied the df data are stored in __df.xsf__ file.
 +Flag - -atoms used simultaneously with - -df puts positions of atoms of the sample saved in __input_plot.xyz__ into __df_???​.png__. The flag - -bonds ads into the maps also lines connecting close-by atoms.
 +
 +If a flag - -pos is applied for both commands (scanning & plotting) than xy positions of the relaxing Probe Particle (PP) are shown in __xy_???​.png__ as a red dots, while the gray scale on the background maps represent z position of the PP (brighter - higher). ​
 +
 +===== Tests =====
 +
 +Examples of df simulation is already in the downloaded/​cloned repository in folder __examples/​__. You should try to run these examples before going to your own stuff, in order to see that the code is working on your machine.
 +
 +  ​
 +
 +===== Scans with different charge (Q), lateral stiffness (K) or oscillation amplitude (A) =====
 +
 +A scan with different charge (Q) and/or lateral stiffness (K) than those written in __params.ini__ can be calculated via running (be aware, that for Q ≠ 0.0, you need to have precalculated electrostatic forces):
 +
 +  python PATH_TO_YOUR_PROBE_PARTICLE_MODEL/​relaxed_scan.py -q (Q) -k (K)
 +
 +It will create a new folder __Q?​.??​K?​.??/​__ where will be stored the results from the new run. A df map for wanted oscillation amplitude (A) can be then created by:
 +
 +  python PATH_TO_YOUR_PROBE_PARTICLE_MODEL/​plot_results.py --df -q (Q) -k (K) -a (A)
 +
 +The results will be saved in subfolder __Amp?​.??/​__.
 +
 +Also scans over ranges of (Q),(K) and (A) can be done, via: 
 +
 +  python PATH_TO_YOUR_PROBE_PARTICLE_MODEL/​relaxed_scan.py --krange min max nK  --qrange min max nQ
 +
 +  python PATH_TO_YOUR_PROBE_PARTICLE_MODEL/​plot_results.py --df --krange min max nK  --qrange min max nQ --arange min max nA
 +
 +===== References =====
 +
 +Prokop Hapala, Georgy Kichin, Christian Wagner, F. Stefan Tautz, Ruslan Temirov, and Pavel Jelínek, Mechanism of high-resolution STM/AFM imaging with functionalized tips, Phys. Rev. B 90, 085421 – http://​journals.aps.org/​prb/​abstract/​10.1103/​PhysRevB.90.085421
 +
 +Prokop Hapala, Ruslan Temirov, F. Stefan Tautz, and Pavel Jelínek, Origin of High-Resolution IETS-STM Images of Organic Molecules with Functionalized Tips, Phys. Rev. Lett. 113, 226101 – http://​journals.aps.org/​prl/​abstract/​10.1103/​PhysRevLett.113.226101